Blood Test Can Aid Spinal Cord Injury Recovery

They are often life-altering conditions requiring intensive care, yet early diagnosis and prognosis are difficult due to highly variable clinical presentations. Neurological exams, typically used to assess severity, can be unreliable in the first days as they depend on patient responsiveness. Researchers have now shown that routine hospital blood tests could provide early, accurate insights into recovery and survival for spinal cord injury patients.

A study, led by researchers the University of Waterloo (Ontario, Canada), investigated whether standard blood samples collected daily in hospitals could help predict outcomes for spinal cord injury patients. Using advanced analytics and machine learning, the team assessed millions of data points from more than 2,600 U.S. patients. They focused on common measurements such as electrolytes and immune cells taken during the first three weeks after injury to identify hidden patterns linked to prognosis.

The findings, published in npj Digital Medicine, revealed that changes in multiple biomarkers over time offered strong predictive value for injury severity and mortality. Unlike early neurological assessments, which may be delayed or inconsistent, these models were accurate as early as one to three days after admission. Prediction accuracy increased as more blood test data accumulated, highlighting the advantage of tracking biomarker trajectories.

Importantly, routine blood tests are cost-effective, widely available, and easy to perform in any hospital, unlike MRIs or specialized biomarker analyses that may not be accessible in many clinical settings. This makes them a practical tool to improve decision-making in emergency and intensive care environments. By predicting outcomes early, doctors can prioritize treatment strategies and allocate resources more effectively.

Going forward, this approach could be integrated into critical care workflows for spinal cord injuries and other trauma cases. The team believes that combining machine learning with everyday diagnostics may expand the role of blood tests in guiding personalized treatment. Future research will refine the models to increase accuracy and adapt them for broader use in clinical practice.

“Prediction of injury severity in the first days is clinically relevant for decision-making, yet it is a challenging task through neurological assessment alone,” said Dr. Abel Torres Espín, lead author of the study. “We show the potential to predict whether an injury is motor complete or incomplete with routine blood data early after injury, and an increase in prediction performance as time progresses.”